Digital image enhancement concerns applying operations to a digital image in order to improve a picture, or restore an original that has been degraded. Digital image enhancement dates back to the origins of digital image processing. Unlike film-based images, digital images can be edited interactively at will, and detail that is indiscernible in an original image can be brought out.
It is often the case that illumination of a subject is uneven, and a scene may appear two dark in some areas while too bright in other areas. Images that appear too dark because of poor illumination or too bright because of over illumination can be restored to accurately reflect the original scene.
Enhancement techniques involve digital image processing and can include inter alia filtering, morphology, composition of layers and random variables. Conventional image processing software often includes a wide variety of familiar editing tools used for enhancing an image, such as edge sharpening, smoothing, blurring, histogram equalization, gamma correction, dithering, color palate selection, paint brush effects and texture rendering. Generally, enhancement techniques include one or more parameters, which a user can dynamically adjust to fine-tune the enhanced image.
Several factors distinguish one enhancement technique over another, including inter alia (i) visual quality of the enhanced image, (ii) robustness, (iii) speed and (iv) ease of use. Requirements (ii) and (iv) generally conflict, since the ability to enhance a variety of different types of imagery generally requires a large number of complex adjustable parameters, where ease of use requires a small number of simple adjustable parameters, each of which is intuitive in its effect on the enhanced image. Regarding requirement (iii), for interactive image editing applications, wherein a user repeatedly adjusts enhancement parameters and watches as the enhanced image changes, if the enhancement operation takes more than a fraction of a second to complete, the performance becomes sluggish, and the capability of accurately fine-tuning the enhancement as desired deteriorates. This speed requirement, together with the proliferation of mega-pixel color images, makes design of an enhancement algorithm quite challenging.
Contrast enhancement is a particular aspect of image enhancement that concerns color variations that are not clearly discernible within an image, because of dark shadows or bright highlights. Because of the eye's relative insensitivity to variations in dark colors and variations in bright colors, important details within an image can be missed. Conventional contrast enhancement involves transfer functions, applied as point-wise operations, for expanding dynamic range in some parts of the color spectrum and compressing dynamic range in other parts, and involves gamma correction for adjusting brightness and contrast.
U.S. Pat. Nos. 6,633,684 and 6,677,959 to James describe contrast enhancement by fitting an original source image, such as an x-ray, between upper and lower low frequency images, and expanding the dynamic color range locally to an interval of color values between the lower and upper frequency image color values. Such expansion serves to visually amplify subtle variations in color value between the lower and upper frequency image color values.